Analysis of Binarized High Frequency Financial Data

A non-trivial probability structure is evident in the binary data extracted from the up/down price movements of very high frequency data such as tick-by-tick data for USD/JPY. In this paper, we analyze the Sony bank USD/JPY rates, ignoring the small deviations from the market price. We then show there is a similar non-trivial probability structure in the Sony bank rate, in spite of the Sony bank rate's having less frequent and larger deviations than tick-by-tick data. However, this probability structure is not found in the data which has been sampled from tick-by-tick data at the same rate as the Sony bank rate. Therefore, the method of generating the Sony bank rate from the market rate has the potential for practical use since the method retains the probability structure as the sampling frequency decreases.Comment: 8pages, 4figures, contribution to the 3rd International Conference NEXT-SigmaPh

Mixtures of compound Poisson processes as models of tick-by-tick financial data

A model for the phenomenological description of tick-by-tick share prices in a stock exchange is introduced. It is based on mixtures of compound Poisson processes. Preliminary results based on Monte Carlo simulation show that this model can reproduce various stylized facts.Comment: 12 pages, 6 figures, to appear in a special issue of Chaos, Solitons and Fractal

Multifractality in the stock market: price increments versus waiting times

By applying the multifractal detrended fluctuation analysis to the high-frequency tick-by-tick data from Deutsche B\"orse both in the price and in the time domains, we investigate multifractal properties of the time series of logarithmic price increments and inter-trade intervals of time. We show that both quantities reveal multiscaling and that this result holds across different stocks. The origin of the multifractal character of the corresponding dynamics is, among others, the long-range correlations in price increments and in inter-trade time intervals as well as the non-Gaussian distributions of the fluctuations. Since the transaction-to-transaction price increments do not strongly depend on or are almost independent of the inter-trade waiting times, both can be sources of the observed multifractal behaviour of the fixed-delay returns and volatility. The results presented also allow one to evaluate the applicability of the Multifractal Model of Asset Returns in the case of tick-by-tick data.Comment: Physica A, in prin

Improved welfare in sheep production.Preventive measures, disease resistance and robustness related to tick-borne fever in sheep

The greatest welfare challenges for sheep during grazing are tick-borne fever (TBF), blow-flies, alveld and predators. Production losses on tick infested pastures are substantial, and it is expected that more than 300 000 lambs/sheep are affected by TBF. In sustainable farming, particularly organic farming, the focus on solving these challenges should be on preventive measures. The dependence on drugs implies a risk for developing resistance. It is therefore of general interest to use preventive methods. However, few efficient preventive measures against tick infection and TBF are available. Thus, there is a need for alternative strategies. The focus of the project will be on: Indirect losses The indirect loss caused by TBF is impaired welfare, growth rate, meat quality and income. National data will provide information on weight, slaughter quality and losses of animals on tick infested pastures and will be used to identify and quantify indirect losses. Increased knowledge about the extent of indirect losses to ticks will increase awareness and motivation for implementing preventive measures. Turn out time on pasture and immunity Lambs on tick infested pasture and sheep brought to tick infested pasture for the first time are at highest risk. Animals will develop immunity after the first infection. The effect of exposing lambs to tick infection at a very early life stage will be tested in an experiment carried out at five farms involving 300 lambs. The hypothesis is that lambs infected early will handle the disease better and will not become seriously ill. Disease resistance There is indication of individual variance in susceptibility against TBF in sheep. Many factors may cause variation in resistance to ticks and TBF between individuals. Exploiting a possible genetic variance between breeds and individuals within breed in such resistance will be done by a controlled challenge test and by analysing data on sheep from ram circles in tick infeste

Intraday Seasonality in Analysis of UHF Financial Data: Models and Their Empirical Verification

The aim of this paper is to outline the typical characteristics of the ultra-high-frequency financial data and to present estimation methods of intraday seasonality of trading activity. Ultra-high-frequency financial data (transactions data or tick-by-tick data) is defined to be a full record of transactions and their associated characteristics. We consider two nonparametric estimation methods: cubic splines and a Nadaraya-Watson kernel estimator of regression. Both approaches are compared empirically and applied to financial data of stocks traded at the Warsaw Stock Exchange.financial UHF data, intraday seasonality, diurnal pattern, cubic splines, kernel estimation.

Stochastic integration for uncoupled continuous-time random walks

Continuous-time random walks are pure-jump processes with several applications in physics, but also in insurance, finance and economics. Based on heuristic considerations, a definition is given for the stochastic integral driven by continuous-time random walks. The martingale properties of the integral are investigated. Finally, it is shown how the definition can be used to easily compute the stochastic integral by means of Monte Carlo simulations.Continuous-time random walks; models of tick-by-tick financial data; stochastic integration

Quasi maximum likelihood estimation and prediction in the compound Poisson ECOGARCH(1,1) model

This paper deals with the problem of estimation and prediction in a compound Poisson ECOGARCH(1,1) model. For this we construct a quasi maximum likelihood estimator under the assumption that all jumps of the log-price process are observable. Since these jumps occur at unequally spaced time points, it is clear that the estimator has to be computed for irregularly spaced data. Assuming normally distributed jumps and a recursion to estimate the volatility allows to define and compute a quasi-likelihood function, which is maximised numerically. The small sample behaviour of the estimator is analysed in a small simulation study. Based on the recursion for the volatility process a one-step ahead prediction of the volatility is defined as well as a prediction interval for the log-price process. Finally the model is fitted to tick-by-tick data of the New York Stock Exchange